Method, system and storage medium for commercial and musical composition recognition and storage

ABSTRACT

A playlist generating method for generating a playlist of content from received broadcasted data is provided. The playlist generating method includes the steps of: extracting features of broadcast content beforehand, storing the features in a content feature file, and storing information relating to the broadcast content in a content information DB; extracting features from the received data, and storing the features in a data feature file; searching for broadcast content of a predetermined kind by comparing data in the content feature file and data in the data feature file; when a name of the predetermined kind of content is determined, storing data corresponding to the broadcast content of the predetermined kind in a search result file; generating a playlist for the broadcast content of the predetermined kind from the search result file and the content information DB.

TECHNICAL FIELD

The present invention relates to a music recognizing method, system anda recording medium storing a music recognizing program. Moreparticularly, the present invention relates to a music recognizingmethod, system and a recording medium storing music recognizing programfor recognizing and storing, in real time, a name of broadcasted musicfrom images or voice information that is broadcasted on TV or FM and thelike.

In addition, the present invention relates to a CM (commercial)recognizing method and system and a recording medium storing a CMrecognizing program. More particularly, the present invention relates toa CM recognizing method, system and a recording medium storing a CMrecognizing program for recognizing and storing, in real time,broadcasted CM from images or voice information broadcasted on TV or FMand the like.

BACKGROUND ART

Conventionally, there is no system for recognizing a music name used incontent of image information or music information broadcasted in realtime, and storing the music name in a storage.

In addition, there is no apparatus for recognizing and storing a CMbroadcasted in real time. In addition, there is no system for comparingand recognizing CM data only by using CM information separated atpredetermined intervals.

As mentioned above, according to the conventional system, there is notechnique to monitor broadcasted music, so that the music name cannot bestored in a storage with time information when the music is broadcasted.The time information can be assigned to a music name only by manually,so that the name of the broadcasted music and the broadcasted timeinformation cannot be provided in real time.

In addition, as to CM, there is no apparatus for recognizing and storinga broadcasted CM from broadcasted images or voice information in realtime. This can be performed manually, so that there is a limit for realtime capability and expansion of scale.

DISCLOSURE OF THE INVENTION

The present invention is contrived in consideration of theabove-mentioned problems. An object of the present invention is toprovide a playlist generating technique for recognizing and storing amusic name of broadcasted music from images and voice information thatare broadcasted on TV and FM and the like.

Another object of the present invention is to provide a playlistgenerating technique for comparing and recognizing target music data inreal time without tag information or watermark information, not only fordata on the air but also for broadcasted data of streaming viacommunication network such as the Internet.

Further, an object of the present invention is to provide a CMrecognizing technique for recognizing and storing broadcasted. CM inreal time from images and voice information on the air on TV and FM andthe like.

The above object can be achieved by a playlist generating method forgenerating a playlist of content from received data, the playlistgenerating method including the steps of:

extracting features of content beforehand, storing the feature in acontent feature file, and storing information relating to the content ina content information DB;

extracting features from the received data, and storing the features ina data feature file;

searching for content by comparing data in the content feature file anddata in the data feature file;

when the data in the content feature file matches the data in the datafeature file, data corresponding to the matched data is stored in asearch result file; and

generating a playlist for the content from the search result file andthe content information DB.

According to the present invention, the time-series playlist can begenerated automatically from broadcasted data on the air and the like.The data feature file is, for example, a broadcast feature file.

In the above configuration, the method may further includes the step of,when data in the data feature file is not included in the contentfeature file, registering the data in the content feature file.

According to the present invention, data can be automatically registeredto the content feature file.

The method may further include the steps of:

making content corresponding to the data that is not included in thecontent feature file to be watched or listened to by a person; and

registering information relating to the content in the contentinformation DB.

According to the present invention, information relating to data in thecontent feature file that is automatically registered can be registered.By using the registered information, the time-series playlist can beautomatically generated.

The method may further include the steps of:

when data in the data feature file is not included in the contentfeature file, making content corresponding to the data to be watched orlistened to by a person;

adding the content to the playlist with information related to thecontent.

According to the present invention, the time-series playlist can becomplemented, so that more accurate playlist can be generated.

The above object can be also achieved by a music recognizing method forrecognizing music from received data, the method including the steps of:

extracting features of music content beforehand, storing the features ina content feature file;

extracting features from the received data, and storing the features ina broadcast feature file;

searching for music by comparing data in the content feature file anddata in the broadcast feature file;

when a music name is determined, the music name is stored in a searchresult file; and

generating a playlist of music from the search result file.

According to the present invention, the time-series playlist on musiccan be automatically generated.

The method may further include the steps of:

determining whether the received data is music or not;

if the data is music, storing information indicating that the data ismusic and the time when the data is received in a music extracted file;

if a music name for data in the broadcast feature file is not determinedin the step of searching for music, storing the data in a music namenot-extracted file; and

generating a music not-detected file from the broadcast feature file,the music extracted file and the music name not-extracted file.

According to the present invention, data that is music but not includedin the time-series playlist can be grasped.

The method may further include the steps of:

making the music stored in the music not-detected file to be listened toby a person;

adding a music name and time of the music stored in the musicnot-detected file in the playlist.

According to the present invention, the time-series playlist can becomplemented, so that more accurate playlist can be generated.

The method may include the step of generating the time-series playlistby using the search result file and the content information DB includinginformation associated with the music name,

wherein the time-series playlist includes time, a name of musicbroadcasted at the time and information related to the name.

According to the present invention, the time-series playlist including amusic name and information relating to the music name can be generatedautomatically.

The method may include the steps of:

receiving broadcasted data in a plurality of areas;

sending data received in each area to a center system;

generating the time-series playlist by using the music recognizingmethod in the center system.

According to the present invention, the time-series playlist relating tocontent broadcasted in broadcasting stations in each area can begenerated automatically.

The above object can be also achieved by a music recognizing method forrecognizing music from received data, the method including the steps of:

extracting features of music content beforehand, storing the features ina content feature file;

receiving broadcasted data in a plurality of areas;

extracting features from the received data, and sending the features asdata of a broadcast feature file to a center system in each area;

in the center system, searching for music by comparing data in thecontent feature file and data in the broadcast feature file;

if a music name is determined, the music name is stored in a searchresult file; and

generating a playlist of music from the search result file.

According to the present invention, since the broadcast feature file isgenerated in each area and is sent to the center, transmission amount tothe center can be decreased.

In the music recognizing method, each of the content information DB andthe information related to the music name includes information relatedto a CM, and the information related to the CM in the contentinformation DB is registered in the content information DB beforehand bythe CM recognizing method, the CM recognizing method further includingthe steps of:

detecting CM data from the received data;

extracting features of the CM data, and storing the features in thebroadcast feature file;

performing data comparison between the broadcast feature file and amaster CM content feature file in which features of CM content arestored beforehand; and

if data in the broadcast feature file does not exist in the master CMcontent feature file, registering the data in the master CM contentfeature file included in the content information DB as a new CM.

According to the present invention, the time-series playlist includingCM information can be generated.

The above object can be also achieved by a CM recognizing method forrecognizing a CM from received data, and storing recognized CM data, themethod including the steps of:

detecting CM data from the received data;

extracting features of the CM data, and storing the features in abroadcast feature file;

performing data comparison between the broadcast feature file and amaster CM content feature file in which features of CM content arestored beforehand; and

if data in the broadcast feature file does not exist in the master CMcontent feature file, registering the data in the master CM contentfeature file as a new CM.

According to the present invention, CM monitoring which wasconventionally performed manually can be performed automatically, sothat CM data applicable foe generating the time-series playlist can beprovided.

In the CM recognizing method, the step of detecting the CM data from thereceived data may include the step of detecting a start point and an endpoint of the CM data,

wherein, when the features of the CM data are extracted, a part of theCM data is cut out to a predetermined length, such that a length fromthe center of the CM data to an end is the same as a length from thecenter to another end.

According to the present invention, input error of the CM data can beabsorbed.

The method may further include the steps of:

displaying CM data that does not exist in the master CM content featurefile as a result of the data comparison; and

registering information relating to the CM data in each database in a CMmanagement database group including the master CM content feature file.

According to the present invention, information relating to CM data thatis automatically registered can be registered in the master CM contentfeature file. By using this information, the time-series playlistincluding information on CM can be generated. Other objects, featuresand advantages of the present invention will become more apparent fromthe following detailed description when read in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a figure for explaining the principle of the presentinvention;

FIG. 2 shows the principle configuration of the present invention;

FIG. 3 shows an outline of a music recognizing system of the presentinvention;

FIG. 4 is a flowchart showing an outline of the operation of the musicrecognizing system of the present invention;

FIG. 5 is a figure showing an outline of the CM recognizing system ofthe present invention;

FIG. 6 is a (first) flowchart showing an outline of the operation of theCM recognizing system of the present invention;

FIG. 7 is a (second) flowchart showing an outline of the operation ofthe CM recognizing system of the present invention;

FIG. 8 shows an outline of the music recognizing system of the firstexample of the present invention;

FIG. 9 shows a flowchart of the music recognizing system of the firstexample of the present invention;

FIG. 10 shows an application example of the first example of the presentinvention;

FIG. 11 shows each file used when a time-series playlist is generatedand relationships among them;

FIG. 12 is a figure for explaining attribute information in thetime-series playlist;

FIG. 13 is a figure for explaining attribute information in thetime-series playlist;

FIG. 14 shows an outline of a CM recognizing system of the secondexample of the present invention;

FIG. 15 is a figure for explaining a cutting method for extractingfeatures of CM data;

FIG. 16 shows a system configuration in the third example of the presentinvention;

FIG. 17 is a flowchart showing operation outline of the system shown inFIG. 16;

FIG. 18 is a flowchart showing the operation of the system in the thirdexample of the present invention;

FIG. 19 shows a storing method of music data;

FIG. 20 shows a storing method of CM data;

FIG. 21 shows processes for generating the content feature file from themusic/CM not-extracted file.

PREFERRED EMBODIMENTS FOR CARRYING OUT THE INVENTION First Embodiment

FIGS. 1 and 2 show the principle of the present embodiment.

As shown in FIG. 1, in this embodiment, features of content areextracted beforehand, and the features are stored in a content featurefile (step 1). A feature of received data is extracted and the featureis stored in a broadcast feature file (step 2). Music is searched for bycomparing data of the content feature file and data of the broadcastfeature file (step 3). When the music is searched for, information onthe music is stored in a search result file (step 4). Then, atime-series playlist of music is generated from the search result fileand is stored (step 5).

As shown in FIG. 2, the principle configuration of the music recognizingsystem of the present embodiment includes a content generating means 300for generating content beforehand, extracting the features of musiccontent and storing the features in a content feature file 320, afeature extracting means 105 for extracting a feature of received dataand storing it in a broadcast feature file 140, a music search means 120for searching for music by comparing data of the content feature file320 and the broadcast feature file 140 and storing the search result ina search result file 150, and a list generating means 200 for generatinga time-series playlist from the search result file 150 and storing it.

FIG. 3 shows an outline of the music recognizing system of the presentinvention. The system shown in the figure includes an on-aircapture/search apparatus 100, a music recognizing/registering apparatus200, and a content generating apparatus 300. These apparatuses arerealized by PCs and the like. Although the present system can berealized by one PC that includes the functions of the present invention,the system includes the three apparatuses in consideration of processloads of PC, performance cost, specification of current hardware and thelike in the embodiment of the present invention.

The on-air capture/search apparatus 100 includes an on-air capture part110, a search part 120, a music extracted file 130, a broadcast featurefile 140, a search result file 150, a music name not-extracted file 160,a music not-detected file 170, and a time data providing part 180.

The on-air capture part 110 successively monitors broadcasted data fromTV, radio broadcasting station, determines whether the monitoredbroadcasted data is music or non-music. When the data is music, theon-air capture part 110 records that the broadcasted data at the time ofmonitoring is music in the music extracted file 130, and extracts thefeature of the broadcasted data in real time at intervals of 7.5seconds, and stores the features in the broadcast feature file 140. Inaddition, the music is stored as digital data in a file (not shown inthe figure) at intervals of 7.5 seconds. The on-air capture part 110performs the above-mentioned processes on the basis of time informationfrom the time data providing part 180. In addition, time stamp isprovided to the captured information and the captured information isstored with the time stamp.

As for the reason for using the interval of 7.5 seconds for detectingmusic in a CM, since the time length of a CM is 15 seconds at theminimum currently, the search of music data can be performed withreliability by using a half of the length as the search interval.

The determination whether music or non-music in the on-air capture part110 can be realized by using a conventional technology for determiningwhether music or non-music (for example, talk and the like), forexample, the conventional technology is “Gakuran” (music/non-musicdetection technology): Japanese patent application No. 8-340293,Japanese patent application No. 10-68158 and the like. The on-aircapture part 110 registers information indicating that the data isdetermined to be music in the music extracted file 130 by using thetechnology.

The search part 120 reads, in a memory, the file in which features ofcontent generated by the content generating apparatus 300, and reads thebroadcast feature file 140. Then, the search part 120 performs matchingbetween the two files and stores the result of matching in the searchresult file 150. Data that does not succeed in the matching is stored inthe music name not-extracted file 160.

As for the above-mentioned search by matching, a learning active searchmethod that is described in Japanese patent No. 3065314 “High speedsignal search method, apparatus and recording medium” can be used. Inthis method, a similarity value between data of the content feature fileand data in the broadcast feature file, and the similarity value iscompared with a threshold, so that the search is performed. The Japanesepatent No. 3065314 can be referred to for the details of the searchmethod.

The music extracted file 130 includes data of the information indicatingmusic with a time stamp. The broadcast feature file that is generated bythe on-air capture part 110 is a TAZ file (binary file). The TAZ file isa file that enables high speed comparison in the learning active search.

The broadcasted content is stored in a WAV file and the like (not shownin the figure).

The on-air capture part 110 automatically captures broadcasted data onthe air, and feature data of the broadcasted data is stored in thebroadcast feature file 140.

Data that is music but that is not detected as music by matching isextracted from the music extracted file 130, the music namenot-extracted file 160 and the broadcast feature file 140, and the datais stored in the music not-detected file 170.

The search result file 150 stores the result of matching between thecontent feature file (after mentioned) generated by the contentgenerating apparatus 300 and the broadcast feature file 140. That is, asa result of matching, information (music name and the like)corresponding to matched data is stored in the search result file, and apiece of data of the broadcast feature file 140 that does not exist inthe content feature file is stored in the music name not-extracted file(after mentioned).

The music checking/registering apparatus 200 includes a music checkingpart 210 and a registering part 220, and outputs the time-seriesplaylist 230.

The music checking part 210 extracts time, music name, artist, program(CM) name, client, product, talent, CD information and the likecorresponding to recognized music by using the search result file 150and the content information DB 330, and passes them to the registeringpart 220.

The registering part 220 registers information extracted by the musicchecking part 210 in the time-series playlist file 230 in the order oftime.

In addition, an operator checks broadcasted content stored in the musicnot-detected file by using the music checking/registering apparatus 200,so that the music is recognized and the data is added to the time-seriesplaylist. The operator listens to the music on the basis of timeinformation in the music not-detected file in which the music iscaptured by the on-air capture part 110 in the form of WAV file and thelike, so that the operator can recognize the broadcasted content.

The content generating apparatus 300 includes a content generating part310, a content feature file 320 and a content information DB 330.

The content generating part 310 obtains content from a medium in whichmusic is recorded, stores the music and attribute data that can beapplied to the content feature file 320 in the content informationdatabase 330. In addition, the content generating part 310 extracts thefeatures of the music, and stores the features in the content featurefile 320 with the music names.

The content feature file 320 is a file generated in the contentgenerating part 310, and stores music names and feature informationcorresponding to the music.

The content information DB 330 stores all attribute data of music by thecontent generating part 310.

Next, the operation of the music recognizing system of the presentinvention will be described. FIG. 4 shows an outline of the operation ofthe music recognizing system of the present invention.

Step 101) The content generating apparatus 300 registers music andattribute data of the music from a recording medium and the like ofmusic content in the content information DB 330. The attribute data are,for example, music name, artist name, program name, client name, productname, talent name and the like.

Step 102) The content generating apparatus 300 extracts the features ofmusic and stores the features in the content feature file 320.

The processes so far are pre-processes for following processes.

Step 103) The on-air capture/search apparatus 100 captures images orvoices on the air. The “images or voices on the air” include images orvoices broadcasted via the Internet.

Step 104) The on-air capture/search apparatus 100 determines whether thecaptured broadcasted data is music or non-music by using a technique fordetermining whether music/non-music.

Step 105) When the data is music in step 103, information indicatingthat the broadcasted data at the time is music is recorded in the musicextracted file 130. “Recording information indicating that thebroadcasted data at the time is music” is, for example, providing a flagindicating music at the time.

Step 106) At the same time of the steps 104 and 105, the feature of themusic is extracted at intervals of 7.5 seconds and the feature is storedin the broadcast feature file 140. In addition, broadcasted data ofmusic is stored in a file (not shown in the figure).

Step 107) Next, the on-air capture/search apparatus 100 launches anapplication for searching for music, and reads information in thecontent feature file 320 that was generated by the content generatingapparatus in step 102 in a memory.

Step 108) The search part 120 of the on-air capture/search apparatus 100also reads the broadcast feature file 140, and performs matching betweenthe two files. At this time, the before-mentioned learning active searchtechnology is used.

Step 109) The result of the matching is stored in the search result file150. The feature data that fails in the matching is stored in the musicname not-extracted file 160.

Step 110) Next, the music checking/registering apparatus 200 reads eachpiece of data in the content information DB 330 from the contentgenerating apparatus 300.

Step 111) In addition, the music checking/registering apparatus 200reads the search result file 150 from the on-air capture/searchapparatus 100.

Step 112) Accordingly, the music checking/registering apparatus 200extracts information such as music name, artist name, captured program,client, product, talent and the like, from data in the search resultfile 150 and data in the content information DB 330, sorts these piecesof information in time series, so as to generate a time series playlistand stores it as the time series playlist DB 230.

Step 113) In addition, the operator checks the music name correspondingto feature data stored in the music not-detected file by listening tothe music, so that the time series playlist is complemented.

Second Embodiment

Next, as the second embodiment of the present invention, a CMrecognizing system for recognizing and storing CM (commercial) frombroadcasted images or voice information on the air on TV or FM/AM willbe described. By referring to CM data generated by the CM recognizingsystem, a playlist that includes CM data can be generated from the musicrecognized in the first embodiment.

FIG. 5 shows an outline of the CM recognizing system of the presentinvention.

The CM recognizing system shown in the figure includes an on-aircapture/search apparatus 400, a CM checking/updating part 500 and a CMmanagement database group 600.

The on-air capture/search apparatus 400 includes a capture part 410, asearch part 420, an FM/AM-CM file 430, a broadcast feature file 440, aCM data file 450 and a TV-CM file 460 and a time data providing part470.

The capture part 410 successively monitors broadcasted data on the airfrom a TV or radio broadcasting station, determines whether thebroadcasted data is a CM or not by determining start and end of the CM.When the broadcasted data is a CM, the monitored CM data is stored inthe TV-CM file 460, or stored in the FM/AM-CM file 430. In addition, thecapture part 410 provides a time stamp to the CM data by using timeinformation provided from the time data providing part 470.

Further, the capture part 410 generates feature data of CM from captureddata and stores the feature data in the broadcast feature file 440. Asdescribed later, when the feature file 440 is generated, in order toabsorb an error of cut points of data cut out by using start and end ofthe CM, the both ends of the CM data are cut out such that both lengthsfrom the center to the ends are the same and the length of thereprocessed CM data becomes a constant length (8.0 seconds). Thereprocessed on-air data are processed into feature data by using thelearning active search technology, and the feature data is stored as theTAZ format. The TAZ file is a file that enables high speed comparisonprocessing in the learning active search.

The search part 420 reads, in the memory, the broadcast feature file 440and a file, in a master CM management database group 600, in whichfeatures of CM are stored. Then, the search part 420 performs matchingbetween the two files, and stores the matching result in the CM datafile 450. The search part 420 uses the learning active search (Japanesepatent No. 3065314 and the like). In this case, as for cut-out CM datain which any CM can not be detected, as a matching result, the CM datais stored in the CM data file 450 in which on-air time is provided asthe name of the CM data.

The FM/AM-CM file 430 stores, as a file of WAV format (only voiceformat), CM data captured by the capture part 410 and that was on theair by FM/AM.

The broadcast feature file 440 stores feature data of the CM extractedfrom the CM data captured by the capture part 410. In addition, thebroadcast feature file 440 is a TAZ file (binary file).

The TV-CM file 460 stores, as a file of AVI format, CM data captured bythe capture part 410 that was broadcasted on TV.

The CM checking/updating part 500 reads the CM data file 450 that storesCM data in which the CM name and the like is not determined. There is ahigh probability that the CM in the CM data file 450 is a new CM. Thus,the operator checks a newly registered CM, and extracts sponsor(client), product name, music name, talent name and the like, and storesthem in files of the CM management database group 600.

The CM management database group 600 includes a CM master 610, a productmaster 620, a talent master 630, a music name master 640, a sponsormaster 650, and a master CM content feature file 660. Data in theproduct master 620, the talent master 630, the music name master 640,the sponsor master 650, and the master CM content feature file 660 areextracted by the CM checking/updating part 500. In addition, thesemasters are master files generated for each attribute of the CM datastored in the CM master 610.

Next, the operation of the above-configuration will be described.

FIGS. 6 and 7 shows flowcharts showing an outline of the operation ofthe CM recognizing system of the present invention.

Step 301) The capture part 410 of the onair capture/search apparatus 400captures broadcasted data on the air.

Step 302) The capture part 410 detects CM data from the capturedbroadcasted data, and extracts the feature by using the before-mentionedmethod from the CM data.

Step 303) The extracted feature is stored in the broadcast feature file440, and goes to step 307.

Step 304, 305) In addition to performing the above-mentioned processes,TV-CM is stored in the TV-CM file 460.

Step 306) In addition, when the extracted CM is a CM that was on the airby FM/AM, the CM is stored in the FM/AM-CM file 430.

Step 307) After the step 303, the search part 420 reads, in the memory,the broadcast feature file 440 and the master CM content feature file660 of the CM management database group 600, and performs the learningactive search in which the two files are compared.

Step 308) By performing the search, if a CM is determined, the processgoes to step 307, then, next search is performed for the data of thebroadcast feature file 440 and the master CM content feature file 660.If the CM is not determined, the process goes to the step 309.

Step 309) If a CM is not determined, the. data is registered in the CMdata file by providing on-air time as the name.

Step 310) The operator checks the CM registered in the CM data file 450by using a conventional software and the like by using the CMchecking/updating part 500.

Step 311) The operator performs maintenance of the CM master 610, andperforms maintenance of masters for each attribute from the CM master610.

Accordingly, a new CM can be registered in the database.

Third Embodiment

In the same way as the first embodiment in which the time seriesplaylist is generated from the recognized music, the time seriesplaylist can be generated from the CM recognized in the secondembodiment.

In addition, in the same way as the example of the CM in the secondembodiment, it is possible to update the content feature file andcontent information DB of music.

Further, it is possible to update the content feature file and thecontent information DB on CM or music in the same way as the secondembodiment while generating the time series playlist in the same way asthe first embodiment. The concrete example will be described later.

In the following, concrete examples for the above-mentioned embodimentswill be described with reference to figures.

EXAMPLE (First Example) Corresponding to the First Embodiment

FIG. 8 shows a configuration of the music recognizing system of thefirst example of the present invention. In each apparatus shown in thefigure, the same numeral is assigned to the same part as that shown inFIG. 3, and the explanation will be omitted.

FIG. 9 shows a flowchart of the operation of the music recognizingsystem of the first example of the present invention. In the following,the music recognizing system of the present invention will be describedwith reference to FIGS. 8 and 9.

As shown in FIG. 8, the music recognizing system includes an on-aircapture/search apparatus 100, a content generating apparatus 300 and amusic checking/registering apparatus 200 that are connected. In theon-air capture/search apparatus 100, a PC 110 for capturing broadcasteddata in real time and a PC 120 for searching the broadcast feature file140 are connected. The content generating apparatus 300 includes a PC310 for managing a content feature file 320 that stores content featuresof music content and a content information DB 330. The musicchecking/registering apparatus 200 is for registering a time-seriesplaylist to a DB.

In a processing system A shown in FIG. 9, the PC 110 captures content onthe air (step 201), and outputs the broadcast feature file 140 from thecaptured data at intervals of 7.5 seconds (step 202). Next, the PC 120obtains data of the music content feature file 320 and the broadcastedfeature file 140 on the memory, and the PC 120 searches them for musicby using the learning active search (step 203), and outputs a searchresult to the search result file 150 (step 205). At this time, if themusic name is not determined by the search, the feature data is storedin the music name not-extracted file (step 207).

After the above-mentioned processes are completed, the musicchecking/registering apparatus 200 generates the time-series playlistfrom the search result of the search result file 150 and the contentinformation DB, and stores it in the DB 230.

In the processing system B shown in FIG. 9, the PC 110 in the on-aircapture/search apparatus 100 determines whether the broadcasted data ismusic or not (step 301). If the data is music, the PC 110 outputsinformation indicating that the data is music and a time stamp to themusic extraction file 130 (step 302). In addition, the music is storedin a WAV file and the like (not shown in the figure) with the timestamp.

Then, the music name not-extracted file 160 (processing system A) andthe music extracted file 130 (processing system B) are merged, so thatthe music name not-detected file 170 for each time can be output (steps208, 209), and the data can be fed back to the search result file 150 bythe operator. Accordingly, the time-series playlist can be complemented.

As for work of the operator, the operator complements necessary dataitems to the search result file while the operator checks content in themusic not-detected file in the PC 120 for searching.

As the content feature file 320 and the broadcast feature file 150, theTAZ file (binary file used for the learning active search) is used.

In the generation of the playlist, the search result file and thecontent information DB including CM master and the like are connected.As an concrete example, an application example will be described later.

In the example shown in FIG. 8, the PC 110 may capture the broadcasteddata of all parts of the country by receiving data from the parts of thecountry, so that the PC 110 can generate the broadcast feature file. Inaddition, by placing the PC 110 in each part of the country, each PC 110may capture broadcasted data at the place and generate a broadcastfeature file and send the broadcast feature file to the PC 120 placed inthe center.

In the following, an application example of the present invention willbe described.

FIG. 10 shows the application example of the example of the presentinvention.

In the figure, the content management center corresponds to the contentgenerating apparatus shown in FIG. 8. The data center corresponds to theon-air capture/search apparatus shown in FIG. 8.

First, the content management center obtains CDs and the like foraudition from record companies, buys DVDs and new CDs from CD shops andthe like. Then, in the content management center, contents are stored inthe content information DB 330 from the recording mediums withattributes of the contents. In addition, features of the contents areextracted and stored in the content feature file 320 (music database inthe example of FIG. 10).

Next, for example, the data center obtains, via a tuner, broadcastedcontent of TV (VHS) or FM and the like obtained via an antenna placed inall parts of the country, or the data center obtains broadcasted contentobtained via a parabola antenna from satellite broadcasting and thelike. The data center digitizes the obtained broadcasted data atintervals of 7.5 seconds, and extracts features of the data, and storesthe features in the broadcast feature file 140. In addition, the datacenter determines whether the data is music or non-music such as talkand the like, and stores the result in the music extracted file 130.

By using the search engine (leaning active search technique), the PC forsearching in the data center searches for music from the content featurefile and the broadcast feature file that are obtained beforehand fromthe content management center, and stores the result in the searchresult file 150.

Accordingly, the PC used as the music checking/registering apparatus 200in the data center generates a time-series playlist by using the searchresult file and the content information DB 330. In the example of FIG.10, music name, artist, program (CM), client, product, talent, CDinformation and the like are registered in a database that may be usedin a Web site and the like in the order of time (using time stampsprovided to the search result file) as the time-series playlist. Inaddition, as for the music that is not searched for, the music is addedby the operator.

FIG. 11 shows each file used when the time-series playlist is generated,and relationships among them.

As shown in the figure, the search result file and the music namenot-extracted file are generated from the broadcast feature file and thecontent feature file. Then, the time-series playlist is generated fromthe search result file and the content information DB.

In addition, the music not-detected file is generated from the musicextracted file and the music name not-extracted file and the like. Bychecking the music name of the music recorded in the file by theoperator, the time-series playlist can be complemented. In addition, asfor the music in which the music name and the like is recognized, themusic can be added to the content feature file as necessary byextracting the feature of the music. Accordingly, when the musiccorresponding to TAZ 4 is captured, the music can be recognized afterthis.

Next, a method for generating the time-series playlist shown in FIG. 10by using the content information DB will be described with reference toFIGS. 12 and 13.

FIG. 12 shows a case where each item is determined at 9 o'clock in theplaylist. As shown in the figure, the content information DB includesvarious databases (master databases) associated with the TAZ data.Therefore, if a music name is determined from TAZ data, each informationat 9 o'clock can be obtained by pursuing from the voice source master toeach master. In addition, the program name can be obtained from thebroadcasting station name and the time. Accordingly, the timeseriesplaylist that includes various related information can be generated.

FIG. 13 shows a case when the time is 11:46. In the same way mentionedabove, various information corresponding to the time can be obtained byusing various masters from the TAZ data.

Next, a simulation result of the music recognizing system of the presentinvention will be described. In the simulation, actuary recorded data ofFM broadcasting (about 35 minutes) is used in which 7 pieces of musicare included as samples. In addition, 193 pieces of CD music are used asdatabase samples in which 6 pieces of music are included in theabove-mentioned broadcasted samples.

As for conditions for the simulation, the broadcasted sample is comparedwith all 193 pieces for each 7.5 seconds (193 pieces=about 20 hours), inwhich the specification of the PC server is 1 CPU (Pentium Xeon 933MHz), 2 GB memory, Linux gcc 291.

As a result of the simulation in the above-mentioned conditions, the 6pieces that should be detected were detected correctly, the time errorwas about within 7.5 seconds, and the search is completed in about 45seconds for the 35 minutes music (2100 seconds). This speed is about 50times (=2100/45) faster than the actual music speed. By using thisspeed, processes for about 9000 pieces of music can be expected inactual time.

In addition, although the above example is described on the basis ofFIGS. 8 and 9, the process shown in FIG. 9 can be realized by a program,so that the program is stored in a disk apparatus connected to acomputer used in the data center and the content management center, orin a portable recording medium such as a floppy disk and a CD-ROM. Then,when the present invention is executed, the program can be installed inthe PC used in the data center or the computer management center, sothat the present invention can be easily realized.

Example Corresponding to the Second Embodiment (Second Example)

In this example, a CM is detected in real time from broadcasted datathat is being broadcasted, so that the CM is recognized and stored. Asmentioned before, by using the thus stored CM data as theabove-mentioned master file, the time-series playlist includinginformation on the CM can be generated.

FIG. 14 shows a configuration of the CM recognizing system of the secondexample of the present invention. In the configuration elements, thesame numeral is assigned to the same configuration part as that of FIG.5, and the explanation will be omitted.

In the CM recognizing system of this example, the CM recognizing systemincludes a capture PC part 410, an on-air capture/search part 400, a CMchecking/updating part 500, and a CM management database 600. Thecapture PC part 410 captures broadcasted content. The on-aircapture/search part 400 includes a learning active search PC 420 forcomparing the broadcast feature file 440 and a master CM content featurefile 660. The CM checking/updating part 500 is used for checking a CMand for updating processes. The CM management database 600 managesvarious master files of the CM.

In the following, the file format in FIG. 14 will be described.

The broadcast feature file 440 is a file of TAZ format in which featuresof both of TV-CM and FM/AM-CM extracted in real time are stored. TheTV-CM file 460 is a file of AVI format in which TV-CM is stored, and theTV-CM file 460 is managed in pairs with content of the broadcast featurefile 440.

The FM/AM-CM file 430 is a file of WAV format in which FM/AM-CM isstored, and is managed in pairs with content of the broadcast featurefile 440.

The CM data file 450 is a file in which a CM to be newly registered isstored. When the CM is TV-CM, the data is stored as an AVI format forexample. When the CM is FM/AM-CM, the data is stored as a WAV format.

The master CM content feature file in the CM management database group600 is stored as the TAZ format.

In the following, the operation in the above-mentioned configurationwill be described with reference to FIGS. 6 and 7.

The capture PC 410 captures content on the air (step 301). Next, thecapture PC 410 obtains the start and the end of the CM by using a CMdetection module. As a technique for the CM detection module, atechnique disclosed in Japanese patent application No. 6-312976 “imagecut point detection method and apparatus” (Tanimura, Tonomura) can beused.

Next, the cut-out CM data is reprocessed in which the CM data is cut-outinto a predetermined length (8.0 seconds) such that the length from thecenter of the CM data to one end is the same as the length from thecenter to another end as shown in FIG. 15 in order to absorb an error ofcut points cut by the CM detection module. The feature of thereprocessed CM data is extracted as the broadcast feature (step 302),and the broadcast feature is stored in the broadcast feature file 440(step 303).

The capture PC 410 stores data on the air by using the CM detectionmodule (steps 304, 305 and 306). When the data on the air is TV, thedata is stored as the AVI format, and when the data is FM/AM, the datais stored as the WAV format.

Next, the learning active search PC 420 reads the broadcast feature file440 and the master CM content feature file 660 of the CM managementdatabase group 600 in the memory, so that the learning active search isperformed (step 307). If a piece of data of the broadcast feature file440 is not registered in the CM content feature file 660, thecorresponding CM is registered in the CM data file 450 (step 309). Inaddition, if the data in the broadcast feature file 440 is notregistered in the CM content feature file 660, the data is registered inthe master CM content feature file 660 unconditionally.

Next, checking of the CM registered in the CM data file 450 is performedin the CM checking/updating part 500 (step 310). The checking of the CMis performed by using an existing software. The CM is finally registeredin the CM master 610 by adding various additional information by theoperator. Further, by using attributes of the CM registered in the CMmaster 610, the product master 620, the talent master 630, the musicname master 640, the sponsor master 650, the master CM content featurefile 660 are updated by corresponding data (step 311).

In the above-mentioned example, although the above example is describedon the basis of flowcharts in FIGS. 6 and 7, the process shown in FIG. 6can be realized by a program, so that the program is stored in a diskapparatus connected to a computer used in the on-air capture/searchapparatus, or stored in a portable recording medium such as a floppydisk and CD-ROM and the like. Then, when the present invention isexecuted, the program can be installed in the PC (capture PC, learningactive search PC) used in the on-air capture/search apparatus, so thatthe present invention can be easily realized.

In the above example, although processes are shown in which broadcasteddata on the air from a broadcasting station of TV, FM/AM and the like iscaptured, and recognized and stored, the present invention is notlimited to this example. The same processes as the above-mentionedprocesses can be applied to data transmitted via a communication networksuch as the Internet and the like.

In the above example, although the feature of the music is extracted atintervals of 7.5 seconds and the feature of CM is extracted at intervalsof 8 seconds, these are merely examples and the present invention is notlimited to these examples.

Example Corresponding to the Third Embodiment (Third Example)

Next, an example will be described in which, while the playlist isgenerated in the same way as the first example by capturing music andCM, data is registered in the content generating part in the same way asthe second example.

FIG. 16 shows a system configuration in the third example.

As shown in FIG. 16, the music/CM recognizing system in the thirdexample includes a capture part/search apparatus 700, a contentgenerating apparatus 800, and a music/CM checking/registering apparatus900. The capture part/search apparatus 700 captures broadcasted contentand searches for music and CM. The content generating apparatus 800generates a content information DB. The music CM checking/registeringapparatus 900 generates the time-series playlist from the search resultfile and the content information DB, and registers attribute informationof newly recognized music and CM in the content generating apparatus800.

The on-air capture/search apparatus 700 includes an on-air capture part710, a search part 720, a music/CM extracted file 730, a broadcastfeature file 740, a search result file 750, a music/CM not-extractedfile 760, a music/CM not-detected file 770, and a content feature filegenerating part 780. The content generating apparatus includes a contentgenerating part 780, a content feature file 820 and a contentinformation DB 830.

FIG. 17 is a flowchart showing outline operation of the system shown inFIG. 16. The outline operation will be described with reference to FIG.17.

The content generating apparatus 800 extracts features of music and CM,and stores the features as the content feature file (step 401). In theon-air capture/search apparatus 700, the on-air capture part 710captures broadcasted content including music and CM and stores thecontent as the AVI file, WAV file and the like, and extracts features ofthe content, and stores the feature in the broadcast feature file 740(step 402). Next, music and CM are searched for by using the contentfeature file 820 and the broadcast feature file 740 (step 403). When themusic or the CM is determined, information on the music or the CM isstored in the search result file (step 404), so that the time seriesplaylist is generated (step 405). If the music or the CM is notdetermined, the feature data by which the music or the CM is notdetermined is stored in the music/CM not-extracted file (step 406).Then, a content feature file corresponding to the music or the CM isgenerated, so that the content feature file is automatically registeredin the content feature file 820 in the content generating apparatus 800(step 407).

Next, the above-mentioned processes will be described in more detail byusing a flowchart of the processes in the on-air capture part/searchapparatus 700 shown in FIG. 18.

As shown in FIG. 18, the processes by the on-air capture part/searchapparatus 700 in this example can be divided into a process system 1 forperforming search for music and CM, a process system 2 for performingmusic detection, music determination and storing, and a process system 3for performing CM detection and storing.

In the process system 2, in the same way as the first example, it isdetermined whether the broadcast content is music or not, a musicextracted file is generated, and music data is stored as a WAV file andthe like (steps 501-503). FIG. 19 shows a storing method of music data.Accordingly, the part determined to be music is stored at intervals of7.5 seconds.

In the process system 3, in the same way as the second example, the CMextracted file is generated by detecting cut points in broadcasted data,and the CM data is stored as the AVI file and the like (steps 511-513).FIG. 20 shows the manner. Accordingly, the CM part between the cutpoints is stored.

The CM extracted file is similar to the music extracted file in music.In the CM extracted file, information indicating that the data is CM andthe time are recorded.

In the process system 1, in the same way as the first example as formusic, and in the same way as the second example as for CM, the featureis extracted and music or CM is searched for (steps 521, 522).

When a name of music or CM is determined, the search result file 750 isgenerated (step 523). If the name of music or CM is not determined, thedata is stored in the music/CM not-extracted file (step 524), and thecontent feature file is automatically generated by using the data (step525), so as to be provisionally registered in the content feature file520.

FIG. 21 shows processes for generating the content feature file from themusic/CM not-extracted file. Accordingly, the content feature file isgenerated from data files (AVI or WAV) of music or CM corresponding todata in the music/CM not-extracted file.

In the same way as the first example, the music/CM not-detected file isgenerated from the music/CM not-extracted file and the music/CMextracted file and the like (step 526). The operator checks the music orthe CM and the time-series playlist is complemented by the recognizedmusic or CM (step 527). Further, by using the result of checking,various databases in the content generating apparatus are updated (musicname, artist name and the like are associated with a TAZ file), so thatthe provisionally registered content feature file is formally registered(step 528).

By performing the above-mentioned processes, data of the content featurefile from which the playlist can be generated can be added andinformation on music and CM can be registered, while the time-seriesplaylist is generated.

As mentioned above, according to the present invention for recognizingmusic in real time, broadcasted data on the air (music and the like usedfor CM) is digitized and the feature is extracted at intervals of 7.5seconds, and the feature is compared with the content feature fileprepared beforehand, so that the music name can be stored in a storagewith information of time when the music is broadcasted as thetime-series list. Accordingly, the time-series playlist can be obtainedin which music name, artist name, program (CM), client, product, talent,CD information and the like are included, so that meaningful informationresult can be obtained. This information can be utilized as marketinginformation for a sales target.

As for the reason for digitizing the data at intervals of 7.5 secondsfor extracting the feature, since the time for broadcasting a CM isgenerally 15 seconds at the minimum currently, a half of 15 seconds isused for the interval for digitizing and extracting feature forperforming search with reliability. Therefore, the time interval fordigitizing can be changed from 7.5 seconds to other value according tothe kind of content.

In addition, the CMs are conventionally monitored manually forextraction. On the other hand, according to the present invention, itbecomes possible to automatically recognize CMs. In addition, CM data onthe air in TV and FM/AM can be registered without tag information orwatermark information. The CM data can be used for generating thetime-series playlist.

In addition, according to the present invention, since data in whichmusic name and the like can not be determined can be automaticallyregistered in the content generating apparatus in the process forgenerating the time-series playlist, data in the database in the contentgenerating apparatus can be expanded, so that more accurate time-seriesplaylist can be generated.

The present invention is not limited to the specifically disclosedembodiments, and variations and modifications may be made withoutdeparting from the scope of the invention.

1. A music recognizing method for recognizing music from received data,the method comprising the steps of: extracting features of music contentbeforehand, storing the features and corresponding music names in acontent feature file; extracting a feature from the received data, andstoring the feature and a time in a broadcast feature file; searchingfor a music name of the feature in the broadcast feature file bycomparing data in the content feature file and data in the broadcastfeature file, wherein the music name corresponds to a feature, in thecontent feature file, the same as the feature in the broadcast featurefile; when the music name is determined, the music name and the timecorresponding to the feature, in the broadcast feature file, thatcorresponds to the music name are stored in a search result file; andgenerating a time-series playlist of music using the search result fileand a content information database (DB) including information associatedwith the music name, wherein the time-series playlist includes the time,the music name of music broadcasted at the time and informationassociated with the music name.
 2. The music recognizing method asclaimed in claim 1, the method further comprising the steps of:determining whether the received data is music or not; if the data ismusic, storing information indicating that the data is music and thetime when the data is received in a music extracted file; if a musicname for data in the broadcast feature file is not determined in thestep of searching for music, storing the data in a music namenot-extracted file; and generating a music not-detected file from thebroadcast feature file, the music extracted file and the music namenot-extracted file.
 3. The music recognizing method as claimed in claim2, the method further comprising the steps of: making the music storedin the music not-detected file to be listened to by a person; adding amusic name and a time of the music stored in the music not-detected filein the playlist.
 4. The music recognizing method as claimed in claim 1,the method comprising the steps of: receiving broadcasted data in aplurality of areas; sending data received in each area to a centersystem; generating the time-series playlist by using the musicrecognizing method in the center system.
 5. The music recognizing methodas claimed in claim 1, wherein each of the content information DB andthe information related to the music name includes information relatedto a commercial (CM), and the information related to the CM in thecontent information DB is registered in the content information DBbeforehand by the CM recognizing method, the CM recognizing methodfurther comprising the steps of: detecting CM data from the receiveddata; extracting features of the CM data, and storing the features inthe broadcast feature file; performing data comparison between thebroadcast feature file and a master CM content feature file in whichfeatures of CM content are stored beforehand; and if data in thebroadcast feature file does not exist in the master CM content featurefile, registering the data in the master CM content feature fileincluded in the content information DB as a new CM.
 6. A musicrecognizing method for recognizing music from received data, the methodcomprising the steps of: extracting features of music contentbeforehand, storing the features and corresponding music names in acontent feature file; receiving broadcasted data in a plurality ofareas; extracting a feature from the received data, and sending thefeature and a time as data of a broadcast feature file to a centersystem in each area; in the center system, searching for music name ofthe feature in the broadcast feature file by comparing data in thecontent feature file and data in the broadcast feature file, wherein themusic name corresponds to a feature, in the content feature file, thesame as the feature in the broadcast feature file; when the music nameis determined, the music name and the time corresponding to the feature,in the broadcast feature file, that corresponds to the music name arestored in a search result file; and generating a time-series playlist ofmusic using the search result file and a content information databaseincluding information associated with the music name, wherein thetime-series playlist includes the time, the music name of musicbroadcasted at the time and information associated with the music name.7. A commercial (CM) recognizing method for recognizing CM data fromreceived data, and storing the recognized CM data, the method comprisingthe steps of: detecting the CM data from the received data; extractingfeatures of the CM data, and storing features in a broadcast featurefile; performing data comparison between the broadcast feature file anda master CM content feature file in which features of CM content arestored beforehand; and if data in the broadcast feature file does notexist in the master CM content feature file, registering the data in themaster CM content feature file as a new CM, the step of detecting the CMdata from the received data comprising the steps of: detecting a startpoint and an end point of the CM data, by using a CM detecting modulefor detecting cut points in images; and cutting out a part of the CMdata to obtain a predetermined length such that a length from the centerof the CM data to an end is the same as a length from the center toanother end so as to extract the features of the CM data from the partof the predetermined length in the extracting step.
 8. The CMrecognizing method as claimed in claim 7, the method further comprisingthe steps of: displaying CM data that does not exist in the master CMcontent feature file as a result of the data comparison; and registeringinformation relating to the CM data in each database in a CM managementdatabase group including the master CM content feature file.
 9. A musicrecognizing system for recognizing music from received data, the systemcomprising: means for obtaining data of a content feature file in whichfeatures and corresponding music names of music content are stored;means for extracting a feature from the received data, and storing thefeature and a time in a broadcast feature file; means for searching fora music name of the feature in the broadcast feature file by comparingdata in the content feature file and data in the broadcast feature file,wherein the music name corresponds to a feature, in the content featurefile, the same as the feature in the broadcast feature file; means for,when the music name is determined, storing the music name and the timecorresponding to the feature, in the broadcast feature file, thatcorresponds to the music name in a search result file; and means forgenerating a time-series playlist of music using the search result fileand a content information database including information associated withthe music name, wherein the time-series playlist includes the time, themusic name of music broadcasted at the time and information associatedwith the music name.
 10. The music recognizing system as claimed inclaim 9, the system further comprising: means for determining whetherthe received data is music or not; means for, if the data is music,storing information indicating that the data is music and the time whenthe data is received in a music extracted file; means for, if a musicname of data in the broadcast feature file is not determined, storingthe data in a music name not-extracted file; and means for generating amusic not-detected file from the broadcast feature file, the musicextracted file and the music name not-extracted file.
 11. The musicrecognizing system as claimed in claim 10, the system furthercomprising: means for making the music stored in the music not-detectedfile to be listened to by a person; means for adding a music name and atime on the music stored in the music not-detected file in the playlist.12. A music recognizing system for recognizing music from received data,the system comprising: a plurality of apparatuses for receivingbroadcasted data in a plurality of areas; a center system for receivingdata received in each area from each apparatus, the center systemcomprising: means for obtaining data of a content feature file in whichfeatures and corresponding music names of music content are stored;means for extracting feature from the received data, and storing thefeature and a time in a broadcast feature file; means for searching fora music name of the feature in the broadcast feature file by comparingdata in the content feature file and data in the broadcast feature file,wherein the music name corresponds to a feature, in the content featurefile, the same as the feature in the broadcast feature file; means for,when the music name is determined, storing the music name and the timecorresponding to the feature, in the broadcast feature file, thatcorresponds to the music name in a search result file; and means forgenerating a time-series playlist of music using the search result fileand a content information database including information associated withthe music name, wherein the time-series playlist includes the time, themusic name of music broadcasted at the time and information with themusic name.
 13. A music recognizing system for recognizing music fromreceived data, the system comprising: a plurality of apparatuses forreceiving broadcasted data and extracting features of the broadcasteddata in a plurality of areas; a center system for receiving the featuresof data received in each area from each apparatus, the center systemcomprising: means for obtaining data of a content feature file in whichfeatures and corresponding music names of music content are stored;means for extracting a feature from the received data, and storing thefeature and a time in a broadcast feature file; means for searching fora music name of the feature in the broadcast feature file by comparingdata in the content feature file and data in the broadcast feature file,wherein the music name corresponds to a feature, in the content featurefile, the same as the feature in the broadcast feature file; means for,when the music name is determined, storing the music name and the timecorresponding to the feature, in the broadcast feature file, thatcorresponds to the music name in a search result file; and means forgenerating a time-series playlist of music using the search result fileand a content information database including information associated withthe music name, wherein the time-series playlist includes the time, themusic name of music broadcasted at the time and information with themusic name.
 14. A commercial (CM) recognizing system for recognizing CMdata from received data, and storing the recognized CM data, the systemcomprising: means for detecting the CM data from the received data;means for extracting features of the CM data, and storing the featuresin a broadcast feature file; means for performing data comparisonbetween the broadcast feature file and a master CM content feature filein which features of CM content are stored beforehand; and means for, ifdata in the broadcast feature file does not exist in the master CMcontent feature file, registering the data in the master CM contentfeature file as a new CM; the means for detecting the CM data from thereceived data comprising means for detecting a start point and an endpoint of the CM data by using a CM detection module for detecting cutpoints in images; and cutting out a part of the CM data to obtain apredetermined length such that a length from the center of the CM datato an end is the same as a length from the center to another end so asto extract the features of the CM data from the part of thepredetermined length in the extracting step.
 15. The CM recognizingsystem as claimed in claim 14, the system further comprising: means fordisplaying CM data that does not exist in the master CM content featurefile as a result of the data comparison; and means for registeringinformation relating to the CM data in each database in a CM managementdatabase group including the master CM content feature file.
 16. Acomputer readable medium recording program code for causing a computerto perform processes for recognizing music from received data, thecomputer readable medium comprising: program code means for extracting afeature and a time from the received data, and storing the feature and atime in a broadcast feature file; program code means for searching for amusic name of the feature in the broadcast feature file by comparingdata in a content feature file, in which features and correspondingmusic names of music content are stored, and data in the broadcastfeature file, wherein the music name corresponds to a feature, in thecontent feature file, the same as the feature in the broadcast featurefile; program code means for, when the music name is determined, storingthe music name and the time corresponding to the feature, in thebroadcaste feature file, that corresponds to the music name in a searchresult file; and program code means for generating a time-seriesplaylist of music using the search result file and a content informationdatabase including information associated with the music name, whereinthe time-series playlist includes the time, the music name of musicbroadcasted at the time and information with the music name.
 17. Thecomputer readable medium as claimed in claim 16, the computer readablemedium further comprising: program code means for determining whetherthe received data is music or not; program code means for, if the datais music, storing information indicating that the data is music and thetime when the data is received in a music extracted file; program codemeans for, if a music name of the data in the broadcast feature file isnot determined, storing the data in a music name not-extracted file; andprogram code means for generating a music not-detected file from thebroadcast feature file, the music extracted file and the music namenot-extracted file.
 18. The computer readable medium as claimed in claim17, the computer readable medium further comprising: program code meansfor making the music stored in the music not-detected file to belistened to by a person; program code means for adding a music name anda time on the music stored in the music not-detected file in theplaylist.
 19. A computer readable medium recording program code forcausing a computer to perform processes for recognizing music fromreceived data, the computer readable medium comprising: program codemeans for receiving a feature and a time of broadcasted data received ineach area as a broadcast feature file from each apparatus; program codemeans for searching for a music name by comparing data in a contentfeature file, in which features and corresponding music names of musiccontent are stored, and data in the broadcast feature file, wherein themusic name corresponds to a feature, in the content feature file, thesame as the feature in the broadcast feature file; program code meansfor, when the music name is determined, storing the music name and thetime corresponding to the feature, in the broadcast feature file, thatcorresponds to the music name in a search result file; and program codemeans for generating a time-series playlist of music using the searchresult file and a content information database including informationassociated with the music name, wherein the time-series playlistincludes the time, the music name of music broadcasted at the time andinformation with the music name.
 20. A computer readable mediumrecording program code for causing a computer to perform processes forrecognizing commercial (CM) data from received data, and storing therecognized CM data, the computer readable medium comprising: programcode means for detecting the CM data from the received data; programcode means for extracting features of the CM data, and storing thefeatures in a broadcast feature file; program code means for performingdata comparison between the broadcast feature file and a master CMcontent feature file in which features of CM content are storedbeforehand; and program code means for, if data in the broadcast featurefile does not exist in the master CM content feature file, registeringthe data in the master CM content feature file as a new CM; the programcode means for detecting the CM data from the received data comprising;program code means for detecting a start point and an end point of theCM data by using a CM detection module for detecting cut points inimages; and cutting out a part of the CM data to obtain a predeterminedlength such that a length from the center of the CM data to an end isthe same as a length from the center to another end so as to extract thefeatures of the CM data from the part of the predetermined length in theextracting step.
 21. The computer readable medium as claimed in claim20, the computer readable medium further comprising: program code meansfor displaying CM data that does not exist in the master CM contentfeature file as a result of the data comparison; and program code meansfor registering information relating to the CM data in each database ina CM management database group including the master CM content featurefile.